@ARTICLE{eichinger10from,
author = {Frank Eichinger and David Kramer and Klemens B{\"o}hm and Wolfgang
Karl},
title = {{F}rom {S}ource {C}ode to {R}untime {B}ehaviour: {S}oftware {M}etrics
{H}elp to {S}elect the {C}omputer {A}rchitecture},
journal = {{K}nowledge-{B}ased {S}ystems},
year = {2010},
volume = {23},
pages = {343--349},
number = {4},
abstract = {The decision which hardware platform to use for a certain application
is an important problem in computer architecture. This paper reports
on a study where a data-mining approach is used for this decision.
It relies purely on source-code characteristics, to avoid potentially
expensive programme executions. One challenge in this context is
that one cannot infer how often functions that are part of the application
are typically executed. The main insight of this study is twofold:
(a) Source-code characteristics are sufficient nevertheless. (b)
Linking individual functions with the runtime behaviour of the programme
as a whole yields good predictions. In other words, while individual
data objects from the training set may be quite inaccurate, the resulting
model is not.},
doi = {10.1016/j.knosys.2009.11.014}
}